R Notebook

Load libraries

library(car)
library(knitr)
library(rmdformats)
library(ggplot2)
library(ggpubr)
library(GGally)

library(tidyverse)
library(lme4)
library(lmerTest)
library("MuMIn")
library(lmtest)
library(boot)

Read datasets

AllSubs_NeuralActivation <- read.csv('/Users/luisalvarez/Documents/GitHub/RM_Thesis_Neuroforecasting/ProcessedData/AllSubs_NeuralActivation_Aggregate_Combined_clean.csv')

AllSubs_NeuralActivation_Comedy <- read.csv('/Users/luisalvarez/Documents/GitHub/RM_Thesis_Neuroforecasting/ProcessedData/AllSubs_NeuralActivation_Aggregate_Combined_Comedy_clean.csv')

AllSubs_NeuralActivation_Horror <- read.csv('/Users/luisalvarez/Documents/GitHub/RM_Thesis_Neuroforecasting/ProcessedData/AllSubs_NeuralActivation_Aggregate_Combined_Horror_clean.csv')

Notes:

• Have note removed outliers from data.

Create data frames for each model.

# Define aggregate variables. 
All_Gross_W1_log <- log(AllSubs_NeuralActivation$Gross_US_W1_num)
All_Theaters_W1 <- AllSubs_NeuralActivation$Theaters_US_W1_num

Comedy_Gross_W1_log <- log(AllSubs_NeuralActivation_Comedy$Gross_US_W1_num)
Comedy_Theaters_W1 <- AllSubs_NeuralActivation_Comedy$Theaters_US_W1_num

Horror_Gross_W1_log <- log(AllSubs_NeuralActivation_Horror$Gross_US_W1_num)
Horror_Theaters_W1 <- AllSubs_NeuralActivation_Horror$Theaters_US_W1_num
  
M1_df <- data.frame(All_Gross_W1_log, All_Theaters_W1) 
M1_C_df <- data.frame(Comedy_Gross_W1_log, Comedy_Theaters_W1) 
M1_H_df <- data.frame(Horror_Gross_W1_log, Horror_Theaters_W1) 

# Define affect variables.
All_PA <- AllSubs_NeuralActivation$Pos_arousal_scaled
All_NA <- AllSubs_NeuralActivation$Neg_arousal_scaled

Comedy_PA <- AllSubs_NeuralActivation_Comedy$Pos_arousal_scaled
Comedy_NA <- AllSubs_NeuralActivation_Comedy$Neg_arousal_scaled

Horror_PA <- AllSubs_NeuralActivation_Horror$Pos_arousal_scaled
Horror_NA <- AllSubs_NeuralActivation_Horror$Neg_arousal_scaled

M2_df <- data.frame(All_Gross_W1_log, All_PA, All_NA) 
M2_C_df <- data.frame(Comedy_Gross_W1_log, Comedy_PA, Comedy_NA) 
M2_H_df <- data.frame(Horror_Gross_W1_log, Horror_PA, Horror_NA) 

# Define ISC variables. 
All_NAcc_ISC <- AllSubs_NeuralActivation$NAcc_ISC
All_AIns_ISC <- AllSubs_NeuralActivation$AIns_ISC
All_MPFC_ISC <- AllSubs_NeuralActivation$MPFC_ISC

Comedy_NAcc_ISC <- AllSubs_NeuralActivation_Comedy$NAcc_ISC
Comedy_AIns_ISC <- AllSubs_NeuralActivation_Comedy$AIns_ISC
Comedy_MPFC_ISC <- AllSubs_NeuralActivation_Comedy$MPFC_ISC

Horror_NAcc_ISC <- AllSubs_NeuralActivation_Horror$NAcc_ISC
Horror_AIns_ISC <- AllSubs_NeuralActivation_Horror$AIns_ISC
Horror_MPFC_ISC <- AllSubs_NeuralActivation_Horror$MPFC_ISC

# Define models. 
M4_df <- data.frame(All_NAcc_ISC, All_AIns_ISC, All_MPFC_ISC) 
M4_C_df <- data.frame(Comedy_NAcc_ISC, Comedy_AIns_ISC, Comedy_MPFC_ISC) 
M4_H_df <- data.frame(Horror_NAcc_ISC, Horror_AIns_ISC, Horror_MPFC_ISC) 

M5_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_ISC, All_AIns_ISC, All_MPFC_ISC) 
M5_C_df <- data.frame(Comedy_Gross_W1_log, Comedy_PA, Comedy_NA, Comedy_NAcc_ISC, Comedy_AIns_ISC, Comedy_MPFC_ISC) 
M5_H_df <- data.frame(Horror_Gross_W1_log, Horror_PA, Horror_NA, Horror_NAcc_ISC, Horror_AIns_ISC, Horror_MPFC_ISC) 

# Define whole variables. 
All_NAcc_whole <- AllSubs_NeuralActivation$NAcc_whole
All_AIns_whole <- AllSubs_NeuralActivation$AIns_whole
All_MPFC_whole <- AllSubs_NeuralActivation$MPFC_whole

Comedy_NAcc_whole <- AllSubs_NeuralActivation_Comedy$NAcc_whole
Comedy_AIns_whole <- AllSubs_NeuralActivation_Comedy$AIns_whole
Comedy_MPFC_whole <- AllSubs_NeuralActivation_Comedy$MPFC_whole

Horror_NAcc_whole <- AllSubs_NeuralActivation_Horror$NAcc_whole
Horror_AIns_whole <- AllSubs_NeuralActivation_Horror$AIns_whole
Horror_MPFC_whole <- AllSubs_NeuralActivation_Horror$MPFC_whole

# Define models. 
M6_df <- data.frame(All_NAcc_whole, All_AIns_whole, All_MPFC_whole) 
M6_C_df <- data.frame(Comedy_NAcc_whole, Comedy_AIns_whole, Comedy_MPFC_whole) 
M6_H_df <- data.frame(Horror_NAcc_whole, Horror_AIns_whole, Horror_MPFC_whole) 

M7_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_whole, All_AIns_whole, All_MPFC_whole) 
M7_C_df <- data.frame(Comedy_Gross_W1_log, Comedy_PA, Comedy_NA, Comedy_NAcc_whole,
                      Comedy_AIns_whole, Comedy_MPFC_whole) 
M7_H_df <- data.frame(Horror_Gross_W1_log, Horror_PA, Horror_NA, Horror_NAcc_whole,
                      Horror_AIns_whole, Horror_MPFC_whole) 

# Define onset variables. 
All_NAcc_onset <- AllSubs_NeuralActivation$NAcc_onset
All_AIns_onset <- AllSubs_NeuralActivation$AIns_onset
All_MPFC_onset <- AllSubs_NeuralActivation$MPFC_onset

Comedy_NAcc_onset <- AllSubs_NeuralActivation_Comedy$NAcc_onset
Comedy_AIns_onset <- AllSubs_NeuralActivation_Comedy$AIns_onset
Comedy_MPFC_onset <- AllSubs_NeuralActivation_Comedy$MPFC_onset

Horror_NAcc_onset <- AllSubs_NeuralActivation_Horror$NAcc_onset
Horror_AIns_onset <- AllSubs_NeuralActivation_Horror$AIns_onset
Horror_MPFC_onset <- AllSubs_NeuralActivation_Horror$MPFC_onset

# Define models. 
M8_df <- data.frame(All_NAcc_onset, All_AIns_onset, All_MPFC_onset) 
M8_C_df <- data.frame(Comedy_NAcc_onset, Comedy_AIns_onset, Comedy_MPFC_onset) 
M8_H_df <- data.frame(Horror_NAcc_onset, Horror_AIns_onset, Horror_MPFC_onset) 

M9_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_onset, All_AIns_onset, All_MPFC_onset) 
M9_C_df <- data.frame(Comedy_Gross_W1_log, Comedy_PA, Comedy_NA, Comedy_NAcc_onset,
                      Comedy_AIns_onset, Comedy_MPFC_onset) 
M9_H_df <- data.frame(Horror_Gross_W1_log, Horror_PA, Horror_NA, Horror_NAcc_onset,
                      Horror_AIns_onset, Horror_MPFC_onset) 

# Define middle variables. 
All_NAcc_middle <- AllSubs_NeuralActivation$NAcc_middle
All_AIns_middle <- AllSubs_NeuralActivation$AIns_middle
All_MPFC_middle <- AllSubs_NeuralActivation$MPFC_middle

Comedy_NAcc_middle <- AllSubs_NeuralActivation_Comedy$NAcc_middle
Comedy_AIns_middle <- AllSubs_NeuralActivation_Comedy$AIns_middle
Comedy_MPFC_middle <- AllSubs_NeuralActivation_Comedy$MPFC_middle

Horror_NAcc_middle <- AllSubs_NeuralActivation_Horror$NAcc_middle
Horror_AIns_middle <- AllSubs_NeuralActivation_Horror$AIns_middle
Horror_MPFC_middle <- AllSubs_NeuralActivation_Horror$MPFC_middle

# Define models. 
M10_df <- data.frame(All_NAcc_middle, All_AIns_middle, All_MPFC_middle) 
M10_C_df <- data.frame(Comedy_NAcc_middle, Comedy_AIns_middle, Comedy_MPFC_middle) 
M10_H_df <- data.frame(Horror_NAcc_middle, Horror_AIns_middle, Horror_MPFC_middle) 

M11_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_middle, All_AIns_middle, All_MPFC_middle) 
M11_C_df <- data.frame(Comedy_Gross_W1_log, Comedy_PA, Comedy_NA, Comedy_NAcc_middle,
                      Comedy_AIns_middle, Comedy_MPFC_middle) 
M11_H_df <- data.frame(Horror_Gross_W1_log, Horror_PA, Horror_NA, Horror_NAcc_middle,
                      Horror_AIns_middle, Horror_MPFC_middle) 

# Define middle variables. 
All_NAcc_offset <- AllSubs_NeuralActivation$NAcc_offset
All_AIns_offset <- AllSubs_NeuralActivation$AIns_offset
All_MPFC_offset <- AllSubs_NeuralActivation$MPFC_offset

Comedy_NAcc_offset <- AllSubs_NeuralActivation_Comedy$NAcc_offset
Comedy_AIns_offset <- AllSubs_NeuralActivation_Comedy$AIns_offset
Comedy_MPFC_offset <- AllSubs_NeuralActivation_Comedy$MPFC_offset

Horror_NAcc_offset <- AllSubs_NeuralActivation_Horror$NAcc_offset
Horror_AIns_offset <- AllSubs_NeuralActivation_Horror$AIns_offset
Horror_MPFC_offset <- AllSubs_NeuralActivation_Horror$MPFC_offset

# Define models. 
M12_df <- data.frame(All_NAcc_offset, All_AIns_offset, All_MPFC_offset) 
M12_C_df <- data.frame(Comedy_NAcc_offset, Comedy_AIns_offset, Comedy_MPFC_offset) 
M12_H_df <- data.frame(Horror_NAcc_offset, Horror_AIns_offset, Horror_MPFC_offset) 

M13_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_offset, All_AIns_offset, All_MPFC_offset) 
M13_C_df <- data.frame(Comedy_Gross_W1_log, Comedy_PA, Comedy_NA, Comedy_NAcc_offset,
                      Comedy_AIns_offset, Comedy_MPFC_offset) 
M13_H_df <- data.frame(Horror_Gross_W1_log, Horror_PA, Horror_NA, Horror_NAcc_offset,
                      Horror_AIns_offset, Horror_MPFC_offset) 

M14_df <- data.frame(All_Gross_W1_log, All_PA, All_NA, All_NAcc_onset, All_AIns_middle, All_MPFC_offset) 
M14_C_df <- data.frame(Comedy_Gross_W1_log, Comedy_PA, Comedy_NA, Comedy_NAcc_onset,
                      Comedy_AIns_middle, Comedy_MPFC_offset) 
M14_H_df <- data.frame(Horror_Gross_W1_log, Horror_PA, Horror_NA, Horror_NAcc_onset,
                      Horror_AIns_middle, Horror_MPFC_offset) 

Neuroforecasting: First Week US.

M1: Behavioral data

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + scale(Theaters_US_W1_num) + 
    Type:scale(Theaters_US_W1_num), data = AllSubs_NeuralActivation %>% 
    mutate(Type = factor(Type, levels = c("horror", "comedy"))))

Residuals:
     Min       1Q   Median       3Q      Max 
-1.55922 -0.28515  0.02387  0.33475  1.38066 

Coefficients:
                                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)                           16.4641     0.2010  81.928  < 2e-16 ***
Typecomedy                            -0.5646     0.2655  -2.127  0.04310 *  
scale(Theaters_US_W1_num)              1.5282     0.4206   3.633  0.00121 ** 
Typecomedy:scale(Theaters_US_W1_num)  -0.3868     0.4422  -0.875  0.38980    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.688 on 26 degrees of freedom
Multiple R-squared:  0.7944,    Adjusted R-squared:  0.7706 
F-statistic: 33.48 on 3 and 26 DF,  p-value: 4.425e-09

           R2m       R2c
[1,] 0.7759523 0.7759523
[1] 68.40126

M2: Affective data alone

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + scale(Pos_arousal_scaled) + 
    scale(Neg_arousal_scaled) + Type:scale(Pos_arousal_scaled) + 
    Type:scale(Neg_arousal_scaled), data = AllSubs_NeuralActivation %>% 
    mutate(Type = factor(Type, levels = c("horror", "comedy"))))

Residuals:
    Min      1Q  Median      3Q     Max 
-4.1431 -0.4889  0.1215  0.9237  1.9269 

Coefficients:
                                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)                           17.0177     1.1362  14.977 1.12e-13 ***
Typecomedy                            -0.2736     1.8589  -0.147    0.884    
scale(Pos_arousal_scaled)             -0.1825     0.8610  -0.212    0.834    
scale(Neg_arousal_scaled)             -0.3956     0.7695  -0.514    0.612    
Typecomedy:scale(Pos_arousal_scaled)   0.4911     0.9404   0.522    0.606    
Typecomedy:scale(Neg_arousal_scaled)   1.8368     1.8219   1.008    0.323    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1.411 on 24 degrees of freedom
Multiple R-squared:  0.2017,    Adjusted R-squared:  0.03533 
F-statistic: 1.212 on 5 and 24 DF,  p-value: 0.3335

           R2m       R2c
[1,] 0.1728986 0.1728986
[1] 113.0942

M3: Aggregate and affective data alone

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + scale(Pos_arousal_scaled) + 
    scale(Neg_arousal_scaled) + Type:scale(Pos_arousal_scaled) + 
    Type:scale(Neg_arousal_scaled), data = AllSubs_NeuralActivation %>% 
    mutate(Type = factor(Type, levels = c("horror", "comedy"))))

Residuals:
    Min      1Q  Median      3Q     Max 
-4.1431 -0.4889  0.1215  0.9237  1.9269 

Coefficients:
                                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)                           17.0177     1.1362  14.977 1.12e-13 ***
Typecomedy                            -0.2736     1.8589  -0.147    0.884    
scale(Pos_arousal_scaled)             -0.1825     0.8610  -0.212    0.834    
scale(Neg_arousal_scaled)             -0.3956     0.7695  -0.514    0.612    
Typecomedy:scale(Pos_arousal_scaled)   0.4911     0.9404   0.522    0.606    
Typecomedy:scale(Neg_arousal_scaled)   1.8368     1.8219   1.008    0.323    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1.411 on 24 degrees of freedom
Multiple R-squared:  0.2017,    Adjusted R-squared:  0.03533 
F-statistic: 1.212 on 5 and 24 DF,  p-value: 0.3335

           R2m       R2c
[1,] 0.1728986 0.1728986
[1] 113.0942

M4: ISC data alone

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + +scale(NAcc_ISC) + 
    scale(AIns_ISC) + scale(MPFC_ISC) + Type:scale(NAcc_ISC) + 
    Type:scale(AIns_ISC) + Type:scale(MPFC_ISC), data = AllSubs_NeuralActivation %>% 
    mutate(Type = factor(Type, levels = c("horror", "comedy"))))

Residuals:
    Min      1Q  Median      3Q     Max 
-4.5626 -0.3083  0.2310  0.5370  1.9757 

Coefficients:
                           Estimate Std. Error t value Pr(>|t|)    
(Intercept)                16.70980    0.40320  41.443   <2e-16 ***
Typecomedy                 -0.99626    0.54755  -1.819   0.0825 .  
scale(NAcc_ISC)             0.61228    0.56292   1.088   0.2885    
scale(AIns_ISC)            -0.12105    0.38625  -0.313   0.7569    
scale(MPFC_ISC)             0.29369    0.53461   0.549   0.5883    
Typecomedy:scale(NAcc_ISC) -0.80448    0.66711  -1.206   0.2407    
Typecomedy:scale(AIns_ISC)  0.38701    0.62113   0.623   0.5396    
Typecomedy:scale(MPFC_ISC) -0.09906    0.64873  -0.153   0.8800    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1.453 on 22 degrees of freedom
Multiple R-squared:  0.2241,    Adjusted R-squared:  -0.02275 
F-statistic: 0.9078 on 7 and 22 DF,  p-value: 0.5184

           R2m       R2c
[1,] 0.1797455 0.1797455
[1] 116.2379

M5: ISC data + affective data + behavioral data

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + scale(Theaters_US_W1_num) + 
    scale(Pos_arousal_scaled) + scale(Neg_arousal_scaled) + scale(NAcc_ISC) + 
    scale(AIns_ISC) + scale(MPFC_ISC) + Type:scale(Theaters_US_W1_num) + 
    Type:scale(Pos_arousal_scaled) + Type:scale(Neg_arousal_scaled) + 
    Type:scale(NAcc_ISC) + Type:scale(AIns_ISC) + Type:scale(MPFC_ISC), 
    data = AllSubs_NeuralActivation %>% mutate(Type = factor(Type, 
        levels = c("horror", "comedy"))))

Residuals:
     Min       1Q   Median       3Q      Max 
-0.86763 -0.24968 -0.00754  0.28252  1.12778 

Coefficients:
                                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)                          16.01970    0.56278  28.465 3.92e-15 ***
Typecomedy                            1.95895    0.89449   2.190  0.04368 *  
scale(Theaters_US_W1_num)             1.30716    0.44394   2.944  0.00952 ** 
scale(Pos_arousal_scaled)            -0.90672    0.40708  -2.227  0.04063 *  
scale(Neg_arousal_scaled)            -0.25800    0.37397  -0.690  0.50015    
scale(NAcc_ISC)                       0.23035    0.26084   0.883  0.39026    
scale(AIns_ISC)                      -0.28392    0.16844  -1.686  0.11127    
scale(MPFC_ISC)                       0.60359    0.26119   2.311  0.03449 *  
Typecomedy:scale(Theaters_US_W1_num) -0.02941    0.46422  -0.063  0.95027    
Typecomedy:scale(Pos_arousal_scaled)  0.68765    0.45661   1.506  0.15155    
Typecomedy:scale(Neg_arousal_scaled)  2.58832    0.87119   2.971  0.00901 ** 
Typecomedy:scale(NAcc_ISC)            0.07230    0.31912   0.227  0.82363    
Typecomedy:scale(AIns_ISC)            0.18418    0.28584   0.644  0.52849    
Typecomedy:scale(MPFC_ISC)           -0.97877    0.31329  -3.124  0.00654 ** 
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.5868 on 16 degrees of freedom
Multiple R-squared:  0.9079,    Adjusted R-squared:  0.8331 
F-statistic: 12.14 on 13 and 16 DF,  p-value: 6.43e-06

           R2m       R2c
[1,] 0.8447398 0.8447398
[1] 64.29403

M6: Neural whole data alone

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + +scale(NAcc_whole) + 
    scale(AIns_whole) + scale(MPFC_whole) + Type:scale(NAcc_whole) + 
    Type:scale(AIns_whole) + Type:scale(MPFC_whole), data = AllSubs_NeuralActivation %>% 
    mutate(Type = factor(Type, levels = c("horror", "comedy"))))

Residuals:
    Min      1Q  Median      3Q     Max 
-3.6829 -0.3831  0.1901  0.6917  2.0438 

Coefficients:
                             Estimate Std. Error t value Pr(>|t|)    
(Intercept)                   16.5732     0.5184  31.967   <2e-16 ***
Typecomedy                    -0.7712     0.7399  -1.042    0.309    
scale(NAcc_whole)             -0.5606     0.5368  -1.044    0.308    
scale(AIns_whole)              0.5299     0.6150   0.862    0.398    
scale(MPFC_whole)              0.1706     0.5180   0.329    0.745    
Typecomedy:scale(NAcc_whole)   0.3765     0.7021   0.536    0.597    
Typecomedy:scale(AIns_whole)  -0.2614     0.9131  -0.286    0.777    
Typecomedy:scale(MPFC_whole)   0.2835     0.6416   0.442    0.663    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1.44 on 22 degrees of freedom
Multiple R-squared:  0.2374,    Adjusted R-squared:  -0.005294 
F-statistic: 0.9782 on 7 and 22 DF,  p-value: 0.4714

           R2m       R2c
[1,] 0.1910128 0.1910128
[1] 115.7214

M7: Neural whole data + affective data + behavioral data

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + scale(Theaters_US_W1_num) + 
    scale(Pos_arousal_scaled) + scale(Neg_arousal_scaled) + scale(NAcc_whole) + 
    scale(AIns_whole) + scale(MPFC_whole) + Type:scale(Theaters_US_W1_num) + 
    Type:scale(Pos_arousal_scaled) + Type:scale(Neg_arousal_scaled) + 
    Type:scale(NAcc_whole) + Type:scale(AIns_whole) + Type:scale(MPFC_whole), 
    data = AllSubs_NeuralActivation %>% mutate(Type = factor(Type, 
        levels = c("horror", "comedy"))))

Residuals:
     Min       1Q   Median       3Q      Max 
-0.99456 -0.27314 -0.01657  0.28123  0.96246 

Coefficients:
                                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)                          16.25722    0.60777  26.749 1.04e-14 ***
Typecomedy                            1.57410    0.91504   1.720   0.1047    
scale(Theaters_US_W1_num)             1.52817    0.41444   3.687   0.0020 ** 
scale(Pos_arousal_scaled)            -0.20928    0.58243  -0.359   0.7241    
scale(Neg_arousal_scaled)            -0.09669    0.38485  -0.251   0.8048    
scale(NAcc_whole)                    -0.14503    0.26272  -0.552   0.5885    
scale(AIns_whole)                     0.28367    0.28207   1.006   0.3295    
scale(MPFC_whole)                    -0.08670    0.32947  -0.263   0.7958    
Typecomedy:scale(Theaters_US_W1_num) -0.38738    0.43351  -0.894   0.3848    
Typecomedy:scale(Pos_arousal_scaled)  0.27624    0.61052   0.452   0.6570    
Typecomedy:scale(Neg_arousal_scaled)  2.45693    0.88987   2.761   0.0139 *  
Typecomedy:scale(NAcc_whole)          0.51907    0.33703   1.540   0.1431    
Typecomedy:scale(AIns_whole)         -0.47906    0.41378  -1.158   0.2640    
Typecomedy:scale(MPFC_whole)          0.38309    0.37290   1.027   0.3196    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.5955 on 16 degrees of freedom
Multiple R-squared:  0.9052,    Adjusted R-squared:  0.8281 
F-statistic: 11.75 on 13 and 16 DF,  p-value: 8.023e-06

           R2m       R2c
[1,] 0.8404262 0.8404262
[1] 65.17857

M8: Neural onset data alone

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + +scale(NAcc_onset) + 
    scale(AIns_onset) + scale(MPFC_onset) + Type:scale(NAcc_onset) + 
    Type:scale(AIns_onset) + Type:scale(MPFC_onset), data = AllSubs_NeuralActivation %>% 
    mutate(Type = factor(Type, levels = c("horror", "comedy"))))

Residuals:
    Min      1Q  Median      3Q     Max 
-3.6998 -0.4321  0.1720  0.8185  1.6881 

Coefficients:
                             Estimate Std. Error t value Pr(>|t|)    
(Intercept)                   16.9078     0.4518  37.427   <2e-16 ***
Typecomedy                    -1.6161     0.5897  -2.741   0.0119 *  
scale(NAcc_onset)             -0.3234     0.5216  -0.620   0.5415    
scale(AIns_onset)             -0.2077     0.5842  -0.356   0.7256    
scale(MPFC_onset)              0.1921     0.4738   0.405   0.6891    
Typecomedy:scale(NAcc_onset)   0.4906     0.6429   0.763   0.4535    
Typecomedy:scale(AIns_onset)  -0.7656     0.7631  -1.003   0.3266    
Typecomedy:scale(MPFC_onset)   1.0559     0.6864   1.538   0.1382    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1.335 on 22 degrees of freedom
Multiple R-squared:  0.3447,    Adjusted R-squared:  0.1362 
F-statistic: 1.653 on 7 and 22 DF,  p-value: 0.1729

           R2m       R2c
[1,] 0.2852503 0.2852503
[1] 111.1697

M9: Neural onset data + affective data + behavioral data

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + scale(Theaters_US_W1_num) + 
    scale(Pos_arousal_scaled) + scale(Neg_arousal_scaled) + scale(NAcc_onset) + 
    scale(AIns_onset) + scale(MPFC_onset) + Type:scale(Theaters_US_W1_num) + 
    Type:scale(Pos_arousal_scaled) + Type:scale(Neg_arousal_scaled) + 
    Type:scale(NAcc_onset) + Type:scale(AIns_onset) + Type:scale(MPFC_onset), 
    data = AllSubs_NeuralActivation %>% mutate(Type = factor(Type, 
        levels = c("horror", "comedy"))))

Residuals:
     Min       1Q   Median       3Q      Max 
-0.90801 -0.39211  0.06306  0.33282  1.20478 

Coefficients:
                                      Estimate Std. Error t value Pr(>|t|)    
(Intercept)                          17.302775   0.844057  20.500 6.54e-13 ***
Typecomedy                           -0.076805   1.202093  -0.064  0.94985    
scale(Theaters_US_W1_num)             1.562535   0.425321   3.674  0.00205 ** 
scale(Pos_arousal_scaled)            -0.366374   0.499891  -0.733  0.47422    
scale(Neg_arousal_scaled)            -0.741677   0.523649  -1.416  0.17584    
scale(NAcc_onset)                    -0.342762   0.271261  -1.264  0.22448    
scale(AIns_onset)                    -0.841501   0.392021  -2.147  0.04750 *  
scale(MPFC_onset)                     0.268483   0.256281   1.048  0.31038    
Typecomedy:scale(Theaters_US_W1_num) -0.467642   0.452099  -1.034  0.31634    
Typecomedy:scale(Pos_arousal_scaled)  0.205970   0.548225   0.376  0.71207    
Typecomedy:scale(Neg_arousal_scaled)  2.338685   1.039689   2.249  0.03892 *  
Typecomedy:scale(NAcc_onset)          0.520227   0.368203   1.413  0.17685    
Typecomedy:scale(AIns_onset)          0.477460   0.473021   1.009  0.32781    
Typecomedy:scale(MPFC_onset)         -0.009214   0.379665  -0.024  0.98094    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.6614 on 16 degrees of freedom
Multiple R-squared:  0.883, Adjusted R-squared:  0.788 
F-statistic: 9.292 on 13 and 16 DF,  p-value: 3.817e-05

           R2m       R2c
[1,] 0.8064055 0.8064055
[1] 71.47321

M10: Neural middle data alone

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + +scale(NAcc_middle) + 
    scale(AIns_middle) + scale(MPFC_middle) + Type:scale(NAcc_middle) + 
    Type:scale(AIns_middle) + Type:scale(MPFC_middle), data = AllSubs_NeuralActivation %>% 
    mutate(Type = factor(Type, levels = c("horror", "comedy"))))

Residuals:
    Min      1Q  Median      3Q     Max 
-4.0479 -0.3572  0.1014  0.7554  1.8228 

Coefficients:
                              Estimate Std. Error t value Pr(>|t|)    
(Intercept)                   16.77683    0.46169  36.338   <2e-16 ***
Typecomedy                    -0.44119    0.65006  -0.679    0.504    
scale(NAcc_middle)            -0.37128    0.60411  -0.615    0.545    
scale(AIns_middle)             0.13702    0.44866   0.305    0.763    
scale(MPFC_middle)            -0.27542    0.41798  -0.659    0.517    
Typecomedy:scale(NAcc_middle)  0.40053    0.72039   0.556    0.584    
Typecomedy:scale(AIns_middle)  0.98953    0.72471   1.365    0.186    
Typecomedy:scale(MPFC_middle) -0.02962    0.60640  -0.049    0.961    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1.367 on 22 degrees of freedom
Multiple R-squared:  0.3126,    Adjusted R-squared:  0.09385 
F-statistic: 1.429 on 7 and 22 DF,  p-value: 0.2438

           R2m       R2c
[1,] 0.2564756 0.2564756
[1] 112.6066

M11: Neural middle data + affective data + behavioral data

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + scale(Theaters_US_W1_num) + 
    scale(Pos_arousal_scaled) + scale(Neg_arousal_scaled) + scale(NAcc_middle) + 
    scale(AIns_middle) + scale(MPFC_middle) + Type:scale(Theaters_US_W1_num) + 
    Type:scale(Pos_arousal_scaled) + Type:scale(Neg_arousal_scaled) + 
    Type:scale(NAcc_middle) + Type:scale(AIns_middle) + Type:scale(MPFC_middle), 
    data = AllSubs_NeuralActivation %>% mutate(Type = factor(Type, 
        levels = c("horror", "comedy"))))

Residuals:
     Min       1Q   Median       3Q      Max 
-0.90123 -0.34967  0.06124  0.32376  1.04536 

Coefficients:
                                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)                          16.21572    0.60396  26.849  9.8e-15 ***
Typecomedy                            0.84466    0.91724   0.921  0.37079    
scale(Theaters_US_W1_num)             1.81371    0.48933   3.707  0.00192 ** 
scale(Pos_arousal_scaled)            -0.35687    0.43224  -0.826  0.42115    
scale(Neg_arousal_scaled)            -0.30347    0.42833  -0.708  0.48884    
scale(NAcc_middle)                    0.36408    0.39195   0.929  0.36675    
scale(AIns_middle)                    0.22775    0.21781   1.046  0.31127    
scale(MPFC_middle)                   -0.10071    0.21057  -0.478  0.63893    
Typecomedy:scale(Theaters_US_W1_num) -0.65853    0.50875  -1.294  0.21390    
Typecomedy:scale(Pos_arousal_scaled)  0.21594    0.49100   0.440  0.66596    
Typecomedy:scale(Neg_arousal_scaled)  1.31128    0.98801   1.327  0.20307    
Typecomedy:scale(NAcc_middle)        -0.04305    0.43809  -0.098  0.92295    
Typecomedy:scale(AIns_middle)         0.03310    0.45306   0.073  0.94267    
Typecomedy:scale(MPFC_middle)        -0.13681    0.31461  -0.435  0.66947    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.6424 on 16 degrees of freedom
Multiple R-squared:  0.8897,    Adjusted R-squared:    0.8 
F-statistic: 9.924 on 13 and 16 DF,  p-value: 2.481e-05

           R2m       R2c
[1,] 0.8164716 0.8164716
[1] 69.72344

M12: Neural offset data alone

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + +scale(NAcc_offset) + 
    scale(AIns_offset) + scale(MPFC_offset) + Type:scale(NAcc_offset) + 
    Type:scale(AIns_offset) + Type:scale(MPFC_offset), data = AllSubs_NeuralActivation %>% 
    mutate(Type = factor(Type, levels = c("horror", "comedy"))))

Residuals:
    Min      1Q  Median      3Q     Max 
-3.6743 -0.3508  0.1999  0.6837  2.0821 

Coefficients:
                              Estimate Std. Error t value Pr(>|t|)    
(Intercept)                    16.6822     0.4184  39.867   <2e-16 ***
Typecomedy                     -1.1003     0.5997  -1.835   0.0801 .  
scale(NAcc_offset)             -0.2359     0.4577  -0.516   0.6113    
scale(AIns_offset)              0.2008     0.3980   0.505   0.6189    
scale(MPFC_offset)              0.2403     0.5422   0.443   0.6619    
Typecomedy:scale(NAcc_offset)  -0.1149     0.7216  -0.159   0.8750    
Typecomedy:scale(AIns_offset)  -0.5850     0.8097  -0.722   0.4776    
Typecomedy:scale(MPFC_offset)   0.2360     0.6859   0.344   0.7340    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1.467 on 22 degrees of freedom
Multiple R-squared:  0.2093,    Adjusted R-squared:  -0.04228 
F-statistic: 0.8319 on 7 and 22 DF,  p-value: 0.5723

           R2m       R2c
[1,] 0.1672302 0.1672302
[1] 116.8054

M13: Neural offset data + affective data + behavioral data

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + scale(Theaters_US_W1_num) + 
    scale(Pos_arousal_scaled) + scale(Neg_arousal_scaled) + scale(NAcc_offset) + 
    scale(AIns_offset) + scale(MPFC_offset) + Type:scale(Theaters_US_W1_num) + 
    Type:scale(Pos_arousal_scaled) + Type:scale(Neg_arousal_scaled) + 
    Type:scale(NAcc_offset) + Type:scale(AIns_offset) + Type:scale(MPFC_offset), 
    data = AllSubs_NeuralActivation %>% mutate(Type = factor(Type, 
        levels = c("horror", "comedy"))))

Residuals:
     Min       1Q   Median       3Q      Max 
-0.83310 -0.25490 -0.02203  0.31792  0.94449 

Coefficients:
                                      Estimate Std. Error t value Pr(>|t|)    
(Intercept)                          16.392380   0.504429  32.497 4.87e-16 ***
Typecomedy                            0.871610   0.745363   1.169 0.259378    
scale(Theaters_US_W1_num)             1.958277   0.478836   4.090 0.000855 ***
scale(Pos_arousal_scaled)             0.007493   0.426807   0.018 0.986211    
scale(Neg_arousal_scaled)            -0.081703   0.441972  -0.185 0.855661    
scale(NAcc_offset)                   -0.150464   0.174607  -0.862 0.401568    
scale(AIns_offset)                    0.269710   0.163034   1.654 0.117544    
scale(MPFC_offset)                   -0.397626   0.347125  -1.145 0.268855    
Typecomedy:scale(Theaters_US_W1_num) -0.783077   0.491361  -1.594 0.130566    
Typecomedy:scale(Pos_arousal_scaled)  0.160197   0.457094   0.350 0.730558    
Typecomedy:scale(Neg_arousal_scaled)  1.762680   0.779570   2.261 0.038040 *  
Typecomedy:scale(NAcc_offset)         0.030317   0.267425   0.113 0.911151    
Typecomedy:scale(AIns_offset)        -0.227606   0.315011  -0.723 0.480395    
Typecomedy:scale(MPFC_offset)         0.950272   0.379822   2.502 0.023585 *  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.5168 on 16 degrees of freedom
Multiple R-squared:  0.9286,    Adjusted R-squared:  0.8706 
F-statistic:    16 on 13 and 16 DF,  p-value: 9.396e-07

           R2m       R2c
[1,] 0.8776506 0.8776506
[1] 56.67541

M14: Sequence model

Call:
lm(formula = log(Gross_US_W1_num) ~ Type + scale(Theaters_US_W1_num) + 
    scale(Pos_arousal_scaled) + scale(Neg_arousal_scaled) + scale(NAcc_onset) + 
    scale(AIns_middle) + scale(MPFC_offset) + Type:scale(Pos_arousal_scaled) + 
    Type:scale(Neg_arousal_scaled) + Type:scale(NAcc_onset) + 
    Type:scale(AIns_middle) + Type:scale(MPFC_offset), data = AllSubs_NeuralActivation %>% 
    mutate(Type = factor(Type, levels = c("horror", "comedy"))))

Residuals:
     Min       1Q   Median       3Q      Max 
-1.00369 -0.10391  0.00625  0.19037  0.76465 

Coefficients:
                                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)                          16.50986    0.39356  41.950  < 2e-16 ***
Typecomedy                            1.49474    0.69392   2.154 0.045875 *  
scale(Theaters_US_W1_num)             1.20671    0.09297  12.979    3e-10 ***
scale(Pos_arousal_scaled)            -0.26824    0.33773  -0.794 0.437992    
scale(Neg_arousal_scaled)            -0.38981    0.27581  -1.413 0.175606    
scale(NAcc_onset)                    -0.36685    0.19239  -1.907 0.073595 .  
scale(AIns_middle)                    0.41837    0.15054   2.779 0.012859 *  
scale(MPFC_offset)                    0.11172    0.23432   0.477 0.639590    
Typecomedy:scale(Pos_arousal_scaled)  0.35027    0.37689   0.929 0.365707    
Typecomedy:scale(Neg_arousal_scaled)  2.85753    0.71248   4.011 0.000906 ***
Typecomedy:scale(NAcc_onset)          0.69729    0.24036   2.901 0.009942 ** 
Typecomedy:scale(AIns_middle)        -0.46369    0.26794  -1.731 0.101635    
Typecomedy:scale(MPFC_offset)         0.52593    0.27348   1.923 0.071384 .  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.4455 on 17 degrees of freedom
Multiple R-squared:  0.9436,    Adjusted R-squared:  0.9038 
F-statistic: 23.71 on 12 and 17 DF,  p-value: 3.021e-08

           R2m       R2c
[1,] 0.9074989 0.9074989
[1] 47.58297

there are higher-order terms (interactions) in this model
consider setting type = 'predictor'; see ?vif

                          Type      scale(Theaters_US_W1_num)      scale(Pos_arousal_scaled) 
                     18.115472                       1.263053                      16.666114 
     scale(Neg_arousal_scaled)              scale(NAcc_onset)             scale(AIns_middle) 
                     11.115527                       5.408594                       3.311431 
            scale(MPFC_offset) Type:scale(Pos_arousal_scaled) Type:scale(Neg_arousal_scaled) 
                      8.023124                      11.875668                      15.574833 
        Type:scale(NAcc_onset)        Type:scale(AIns_middle)        Type:scale(MPFC_offset) 
                      5.464800                       3.321676                       7.912335